# Set the values for the file names and for the FIPS codes
nhdatafile <- "NHD2016.xlsx"
nhdatafilecsv <- "NHD2016.csv"
usshapefile <- "cb_2014_us_county_5m/cb_2014_us_county_5m.shp"
nhfipscode <- "33"
scdatafile <- "SCGOP2016.csv"
scfipscode <- "45"
# Called in the packages I would need for the assignment
library("shiny")
library("scales")
library("htmlwidgets")
library("dplyr")
## Warning: package 'dplyr' was built under R version 4.0.4
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(tidyverse)
## -- Attaching packages --------------------------------------- tidyverse 1.3.0 --
## v ggplot2 3.3.3 v purrr 0.3.4
## v tibble 3.1.0 v stringr 1.4.0
## v tidyr 1.1.3 v forcats 0.5.1
## v readr 1.4.0
## Warning: package 'tibble' was built under R version 4.0.4
## Warning: package 'tidyr' was built under R version 4.0.4
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x readr::col_factor() masks scales::col_factor()
## x purrr::discard() masks scales::discard()
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(tmap)
## Warning: package 'tmap' was built under R version 4.0.5
library(tmaptools)
## Warning: package 'tmaptools' was built under R version 4.0.5
library(leaflet)
## Warning: package 'leaflet' was built under R version 4.0.5
library(sf)
## Warning: package 'sf' was built under R version 4.0.5
## Linking to GEOS 3.9.0, GDAL 3.2.1, PROJ 7.2.1
library(leaflet.extras)
## Warning: package 'leaflet.extras' was built under R version 4.0.5
library(dplyr)
library(rio)
## Warning: package 'rio' was built under R version 4.0.5
library(sp)
## Warning: package 'sp' was built under R version 4.0.5
# Checked my working directory so I could see where I would have to change it to in order to access the GIS folder
getwd()
## [1] "C:/Users/12403/Documents/DATA 110"
# Changed my working directory and imported the nhdatafilecsv (which I defined as a value in the first chunk)
setwd("~/DATA 110/R_Datasets/GIS/GIS")
nhdata <- import(nhdatafilecsv)
# Decided to just use the columns 'County', 'Clinton', and 'Sanders'
nhdata <- nhdata[,c("County", "Clinton", "Sanders")]
# Added columns for the percentages and margins
nhdata$SandersMarginVotes <- nhdata$Sanders - nhdata$Clinton
nhdata$SandersPct <- (nhdata$Sanders) / (nhdata$Sanders + nhdata$Clinton)
nhdata$ClintonPct <- (nhdata$Clinton) / (nhdata$Sanders + nhdata$Clinton)
nhdata$SandersMarginPctgPoints <- nhdata$SandersPct - nhdata$ClintonPct
# Read in the shapefile for states and counties and loaded in the raster and rdgal packages (which will be used fo rthe qtm command)
setwd("~/DATA 110/R_Datasets/GIS/GIS")
library(raster)
## Warning: package 'raster' was built under R version 4.0.5
##
## Attaching package: 'raster'
## The following object is masked from 'package:tidyr':
##
## extract
## The following object is masked from 'package:dplyr':
##
## select
library(rgdal)
## Warning: package 'rgdal' was built under R version 4.0.5
## rgdal: version: 1.5-23, (SVN revision 1121)
## Geospatial Data Abstraction Library extensions to R successfully loaded
## Loaded GDAL runtime: GDAL 3.2.1, released 2020/12/29
## Path to GDAL shared files: C:/Users/12403/Documents/R/win-library/4.0/rgdal/gdal
## GDAL binary built with GEOS: TRUE
## Loaded PROJ runtime: Rel. 7.2.1, January 1st, 2021, [PJ_VERSION: 721]
## Path to PROJ shared files: C:/Users/12403/Documents/R/win-library/4.0/rgdal/proj
## PROJ CDN enabled: FALSE
## Linking to sp version:1.4-5
## To mute warnings of possible GDAL/OSR exportToProj4() degradation,
## use options("rgdal_show_exportToProj4_warnings"="none") before loading rgdal.
## Overwritten PROJ_LIB was C:/Users/12403/Documents/R/win-library/4.0/rgdal/proj
usgeo <- shapefile("cb_2014_us_county_5m/cb_2014_us_county_5m.shp")
## Warning in rgdal::readOGR(dirname(x), fn, stringsAsFactors = stringsAsFactors, :
## Z-dimension discarded
# Created a quick thematic map (qtm) of the shapefile
qtm(usgeo)
# Viewed the actual data
view(usgeo)
# Decided to look only at the New Hampshire data from the shapefile and creates a qtm of that
nhgeo <- usgeo[usgeo$STATEFP==nhfipscode,]
qtm(nhgeo)
# Viewed the structure of the object
str(nhgeo)
## Formal class 'SpatialPolygonsDataFrame' [package "sp"] with 5 slots
## ..@ data :'data.frame': 10 obs. of 9 variables:
## .. ..$ STATEFP : chr [1:10] "33" "33" "33" "33" ...
## .. ..$ COUNTYFP: chr [1:10] "009" "011" "007" "001" ...
## .. ..$ COUNTYNS: chr [1:10] "00873178" "00873179" "00873177" "00873174" ...
## .. ..$ AFFGEOID: chr [1:10] "0500000US33009" "0500000US33011" "0500000US33007" "0500000US33001" ...
## .. ..$ GEOID : chr [1:10] "33009" "33011" "33007" "33001" ...
## .. ..$ NAME : chr [1:10] "Grafton" "Hillsborough" "Coos" "Belknap" ...
## .. ..$ LSAD : chr [1:10] "06" "06" "06" "06" ...
## .. ..$ ALAND : chr [1:10] "4425927252" "2269220216" "4648216798" "1036582289" ...
## .. ..$ AWATER : chr [1:10] "105375486" "41604851" "90773891" "177039345" ...
## ..@ polygons :List of 10
## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
## .. .. .. ..@ Polygons :List of 1
## .. .. .. .. ..$ :Formal class 'Polygon' [package "sp"] with 5 slots
## .. .. .. .. .. .. ..@ labpt : num [1:2] -71.8 43.9
## .. .. .. .. .. .. ..@ area : num 0.508
## .. .. .. .. .. .. ..@ hole : logi FALSE
## .. .. .. .. .. .. ..@ ringDir: int 1
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## .. .. .. ..@ plotOrder: int 1
## .. .. .. ..@ labpt : num [1:2] -71.8 43.9
## .. .. .. ..@ ID : chr "685"
## .. .. .. ..@ area : num 0.508
## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
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## .. .. .. .. .. .. ..@ hole : logi FALSE
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## .. .. .. .. .. .. ..@ area : num 0.539
## .. .. .. .. .. .. ..@ hole : logi FALSE
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## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
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## .. .. .. .. .. .. ..@ hole : logi FALSE
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## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
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## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
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## .. .. .. ..@ ID : chr "3167"
## .. .. .. ..@ area : num 0.159
## ..@ plotOrder : int [1:10] 3 1 9 8 2 6 5 10 4 7
## ..@ bbox : num [1:2, 1:2] -72.6 42.7 -70.7 45.3
## .. ..- attr(*, "dimnames")=List of 2
## .. .. ..$ : chr [1:2] "x" "y"
## .. .. ..$ : chr [1:2] "min" "max"
## ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slot
## .. .. ..@ projargs: chr "+proj=longlat +datum=NAD83 +no_defs"
# Checked to see whether the county names were the same in both files (nhgeo and nhdata)
str(nhgeo$NAME)
## chr [1:10] "Grafton" "Hillsborough" "Coos" "Belknap" "Rockingham" ...
str(nhdata$County)
## chr [1:10] "Belknap" "Carroll" "Cheshire" "Coos" "Grafton" "Hillsborough" ...
# They weren't, so I changed the county names in nhgeo to plain characters using the as.character command
nhgeo$NAME <- as.character(nhgeo$NAME)
# Ordered the geo and vote datasets by county name and then merged them into the value nhmap using the merge command
nhgeo <- nhgeo[order(nhgeo$NAME),]
nhdata <- nhdata[order(nhdata$County),]
if (identical(nhgeo$NAME,nhdata$County)){
nhmap <- merge(nhgeo, nhdata, by.x = "NAME", by.y = "County")
} else {stop}
# Merged the geo an results data using the merge command
nhmap <- merge(nhgeo, nhdata, by.x = "NAME", by.y = "County")
str(nhmap)
## Formal class 'SpatialPolygonsDataFrame' [package "sp"] with 5 slots
## ..@ data :'data.frame': 10 obs. of 15 variables:
## .. ..$ NAME : chr [1:10] "Belknap" "Carroll" "Cheshire" "Coos" ...
## .. ..$ STATEFP : chr [1:10] "33" "33" "33" "33" ...
## .. ..$ COUNTYFP : chr [1:10] "001" "003" "005" "007" ...
## .. ..$ COUNTYNS : chr [1:10] "00873174" "00873175" "00873176" "00873177" ...
## .. ..$ AFFGEOID : chr [1:10] "0500000US33001" "0500000US33003" "0500000US33005" "0500000US33007" ...
## .. ..$ GEOID : chr [1:10] "33001" "33003" "33005" "33007" ...
## .. ..$ LSAD : chr [1:10] "06" "06" "06" "06" ...
## .. ..$ ALAND : chr [1:10] "1036582289" "2411458935" "1830366195" "4648216798" ...
## .. ..$ AWATER : chr [1:10] "177039345" "158933434" "57990901" "90773891" ...
## .. ..$ Clinton : int [1:10] 3495 3230 5132 2013 6918 28147 12250 22829 8813 2497
## .. ..$ Sanders : int [1:10] 6005 5638 12441 3639 14245 39245 18107 31065 15881 5915
## .. ..$ SandersMarginVotes : int [1:10] 2510 2408 7309 1626 7327 11098 5857 8236 7068 3418
## .. ..$ SandersPct : num [1:10] 0.632 0.636 0.708 0.644 0.673 ...
## .. ..$ ClintonPct : num [1:10] 0.368 0.364 0.292 0.356 0.327 ...
## .. ..$ SandersMarginPctgPoints: num [1:10] 0.264 0.272 0.416 0.288 0.346 ...
## ..@ polygons :List of 10
## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
## .. .. .. ..@ Polygons :List of 1
## .. .. .. .. ..$ :Formal class 'Polygon' [package "sp"] with 5 slots
## .. .. .. .. .. .. ..@ labpt : num [1:2] -71.4 43.5
## .. .. .. .. .. .. ..@ area : num 0.136
## .. .. .. .. .. .. ..@ hole : logi FALSE
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## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
## .. .. .. ..@ Polygons :List of 1
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## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
## .. .. .. ..@ Polygons :List of 1
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## .. .. .. .. .. .. ..@ labpt : num [1:2] -72.3 42.9
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## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
## .. .. .. ..@ Polygons :List of 1
## .. .. .. .. ..$ :Formal class 'Polygon' [package "sp"] with 5 slots
## .. .. .. .. .. .. ..@ labpt : num [1:2] -71.3 44.7
## .. .. .. .. .. .. ..@ area : num 0.539
## .. .. .. .. .. .. ..@ hole : logi FALSE
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## .. .. .. ..@ Polygons :List of 1
## .. .. .. .. ..$ :Formal class 'Polygon' [package "sp"] with 5 slots
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## .. .. .. .. .. .. ..@ hole : logi FALSE
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## .. .. .. ..@ ID : chr "685"
## .. .. .. ..@ area : num 0.508
## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
## .. .. .. ..@ Polygons :List of 1
## .. .. .. .. ..$ :Formal class 'Polygon' [package "sp"] with 5 slots
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## .. .. .. ..@ area : num 0.255
## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
## .. .. .. ..@ Polygons :List of 1
## .. .. .. .. ..$ :Formal class 'Polygon' [package "sp"] with 5 slots
## .. .. .. .. .. .. ..@ labpt : num [1:2] -71.7 43.3
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## .. .. .. .. .. .. ..@ hole : logi FALSE
## .. .. .. .. .. .. ..@ ringDir: int 1
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## .. .. .. ..@ ID : chr "2773"
## .. .. .. ..@ area : num 0.274
## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
## .. .. .. ..@ Polygons :List of 1
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## .. .. .. .. .. .. ..@ labpt : num [1:2] -71.1 43
## .. .. .. .. .. .. ..@ area : num 0.208
## .. .. .. .. .. .. ..@ hole : logi FALSE
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## .. .. .. ..@ labpt : num [1:2] -71.1 43
## .. .. .. ..@ ID : chr "1278"
## .. .. .. ..@ area : num 0.208
## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
## .. .. .. ..@ Polygons :List of 1
## .. .. .. .. ..$ :Formal class 'Polygon' [package "sp"] with 5 slots
## .. .. .. .. .. .. ..@ labpt : num [1:2] -71 43.3
## .. .. .. .. .. .. ..@ area : num 0.11
## .. .. .. .. .. .. ..@ hole : logi FALSE
## .. .. .. .. .. .. ..@ ringDir: int 1
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## .. .. .. ..@ plotOrder: int 1
## .. .. .. ..@ labpt : num [1:2] -71 43.3
## .. .. .. ..@ ID : chr "2676"
## .. .. .. ..@ area : num 0.11
## .. ..$ :Formal class 'Polygons' [package "sp"] with 5 slots
## .. .. .. ..@ Polygons :List of 1
## .. .. .. .. ..$ :Formal class 'Polygon' [package "sp"] with 5 slots
## .. .. .. .. .. .. ..@ labpt : num [1:2] -72.2 43.4
## .. .. .. .. .. .. ..@ area : num 0.159
## .. .. .. .. .. .. ..@ hole : logi FALSE
## .. .. .. .. .. .. ..@ ringDir: int 1
## .. .. .. .. .. .. ..@ coords : num [1:118, 1:2] -72.5 -72.4 -72.4 -72.4 -72.4 ...
## .. .. .. ..@ plotOrder: int 1
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## .. .. .. ..@ ID : chr "3167"
## .. .. .. ..@ area : num 0.159
## ..@ plotOrder : int [1:10] 4 5 2 7 6 3 8 10 1 9
## ..@ bbox : num [1:2, 1:2] -72.6 42.7 -70.7 45.3
## .. ..- attr(*, "dimnames")=List of 2
## .. .. ..$ : chr [1:2] "x" "y"
## .. .. ..$ : chr [1:2] "min" "max"
## ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slot
## .. .. ..@ projargs: chr "+proj=longlat +datum=NAD83 +no_defs"
# Made a static map with Sander's margin votes using the qtm function
qtm(nhmap, "SandersMarginVotes")
## Some legend labels were too wide. These labels have been resized to 0.62, 0.62, 0.62, 0.57, 0.53. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
qtm(nhmap, "SandersMarginPctgPoints")
# Using the tm_shape function I changed the fill color, border line thickness, and added text to the static map itself
tm_shape(nhmap) +
tm_fill("SandersMarginVotes", title="Sanders Margin, Total Votes", palette = "PRGn") +
tm_borders(alpha=.5) +
tm_text("NAME", size=0.8)
## Warning in sp::proj4string(obj): CRS object has comment, which is lost in output
## Some legend labels were too wide. These labels have been resized to 0.62, 0.62, 0.62, 0.57, 0.53. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
# Again, changed the look of the static map by changing its color theme to viridis, its style to classis, and its text.
nhstaticmap <- tm_shape(nhmap) +
tm_fill("SandersMarginVotes", title="Sanders Margin, Total Votes", palette = "viridis") +
tm_borders(alpha=.5) +
tm_text("NAME", size=0.8) +
tm_style("classic")
nhstaticmap
## Warning in sp::proj4string(obj): CRS object has comment, which is lost in output
## Some legend labels were too wide. These labels have been resized to 0.62, 0.62, 0.62, 0.57, 0.53. Increase legend.width (argument of tm_layout) to make the legend wider and therefore the labels larger.
# Saved the map to a jpg gile using the tmap_save command
tmap_save(nhstaticmap, filename="nhdemprimary.jpg")
## Warning in sp::proj4string(obj): CRS object has comment, which is lost in output
## Warning in sp::proj4string(obj): CRS object has comment, which is lost in output
## Map saved to C:\Users\12403\Documents\DATA 110\nhdemprimary.jpg
## Resolution: 1501.336 by 2937.385 pixels
## Size: 5.004452 by 9.791282 inches (300 dpi)
# Created a color palette for the Clinton percentages interactive map (for New Hampshire)
clintonPalette <- colorNumeric(palette = "Blues", domain=nhmap$ClintonPct)
# Created a pop-up window for the map
library(scales)
nhpopup <- paste0("County: ", nhmap$NAME,
", Sanders ", percent(nhmap$SandersPct), " - Clinton ", percent(nhmap$ClintonPct))
# Created the interactive map of Clinton's percentages in New Hampshire
nhmap_projected <- sp::spTransform(nhmap, "+proj=longlat +datum=WGS84")
leaflet(nhmap_projected) %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(stroke=FALSE,
smoothFactor = 0.2,
fillOpacity = .8,
popup=nhpopup,
color= ~clintonPalette(nhmap$ClintonPct))
# Called in the data from South Carolina using the rio::import command
setwd("~/DATA 110/R_Datasets/GIS/GIS")
scdata <- rio::import(scdatafile)
# Created a Soth Carolina shapefile
scgeo <- usgeo[usgeo@data$STATEFP=="45",]
qtm(scgeo)
# Created a column that represented the percent of votes for each candidate and named that value 'winner'
candidates <- colnames(scdata[2:7])
for(i in 2:7){
j = i + 7
temp <- scdata[[i]] / scdata$Total
scdata[[j]] <- temp
colnames(scdata)[j] <- paste0(colnames(scdata)[i], "Pct")
}
winner <- colnames(scdata[2:7])
# Got the winner in each precinct
for(i in 1:nrow(scdata)){
scdata$winner[i] <- names(which.max(scdata[i,2:7]))
}
# Imported spreadsheet with percent of adult population holding at least a 4-year college degree using rio::import command
setwd("C:/Users/12403/Documents/DATA 110/R_Datasets/GIS/GIS")
sced <- rio::import("SCdegree.xlsx")
# Once again checked if the county names were in the same format in both files
str(scgeo$NAME)
## chr [1:46] "Edgefield" "Lee" "Horry" "Allendale" "Marion" "Dorchester" ...
str(scdata$County)
## chr [1:46] "Abbeville" "Aiken" "Allendale" "Anderson" "Bamberg" "Barnwell" ...
# They weren't, so I used the as.character command to change the county names to plain characters in scgeo
scgeo$NAME <- as.character(scgeo$NAME)
# I ordered each dataset by county name
scgeo <- scgeo[order(scgeo$NAME),]
scdata <- scdata[order(scdata$County),]
# Checked it the name and county columns were identical
if (identical(scgeo$NAME,scdata$County )) {
scmap <- merge(scgeo, scdata, by.x = "NAME", by.y = "County")
} else {stop}
# Changed the county names to plain characters in scgeo using the as.character command
scgeo$NAME <- as.character(scgeo$NAME)
# Ordered each data set by county name
scgeo <- scgeo[order(scgeo$NAME),]
scdata <- scdata[order(scdata$County),]
str(scgeo$NAME)
## chr [1:46] "Abbeville" "Aiken" "Allendale" "Anderson" "Bamberg" "Barnwell" ...
str(scdata$County)
## chr [1:46] "Abbeville" "Aiken" "Allendale" "Anderson" "Bamberg" "Barnwell" ...
# Added the election results and renamed the county column from NAME to county
scmap <- merge(scgeo, scdata, by.x = "NAME", by.y = "County")
# Colored by the strength of the win with multiple layers (using the same intensity for all of them)
minpct <- min(c(scdata$`Donald J TrumpPct`, scdata$`Marco RubioPct`, scdata$`Ted CruzPct`))
maxpct <- max(c(scdata$`Donald J TrumpPct`, scdata$`Marco RubioPct`, scdata$`Ted CruzPct`))
# Created leafelt palettes for each layer of the map
trumpPalette <- colorNumeric(palette = "Purples", domain=c(minpct, maxpct))
rubioPalette <- colorNumeric(palette = "Reds", domain = c(minpct, maxpct))
cruzPalette <- colorNumeric(palette = "Oranges", domain = c(minpct, maxpct))
winnerPalette <- colorFactor(palette=c("#984ea3", "#e41a1c"), domain = scmap$winner)
edPalette <- colorNumeric(palette = "Blues", domain=scmap$PctCollegeDegree)
# Created a pop-up
scpopup <- paste0("<b>County: ", scmap$NAME, "<br />Winner: ", scmap$winner, "</b><br /><br />Trump: ", percent(scmap$`Donald J TrumpPct`), "<br />Rubio: ", percent(scmap$`Marco RubioPct`), "<br />Cruz: ", percent(scmap$`Ted CruzPct`), "<br /><br />Pct w college ed: ", sced$PctCollegeDegree, "% vs state-wide avg of 25%")
# Added the projection from the NH map on a Leaflet map
scmap <- sp::spTransform(scmap, "+proj=longlat +datum=WGS84")
# Created a basic interactive map that shows the winner in each county
leaflet(scmap) %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~winnerPalette(scmap$winner),
group="Winners" ) %>%
addLegend(position="bottomleft", colors=c("#984ea3", "#e41a1c"), labels=c("Trump", "Rubio"))
scGOPmap <- leaflet(scmap) %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~winnerPalette(scmap$winner),
group="Winners" ) %>%
addLegend(position="bottomleft", colors=c("#984ea3", "#e41a1c"), labels=c("Trump", "Rubio")) %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~trumpPalette(scmap$`Donald J TrumpPct`),
group="Trump") %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~rubioPalette(scmap$`Marco RubioPct`),
group="Rubio") %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~cruzPalette(scmap$`Ted CruzPct`),
group="Cruz") %>%
addPolygons(stroke=TRUE,
weight=1,
smoothFactor = 0.2,
fillOpacity = .75,
popup=scpopup,
color= ~edPalette(sced$PctCollegeDegree), #this data is in the sced table, not scmaps
group="College degs") %>%
addLayersControl(
baseGroups=c("Winners", "Trump", "Rubio", "Cruz", "College degs"),
position = "bottomleft",
options = layersControlOptions(collapsed = FALSE))
scGOPmap